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English(EN) Real-time virtual circuits for plasma shape control via neural network emulators

神经网络实现聚变反应堆等离子体实时控制

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了神经网络模拟器，为托卡马克聚变反应堆中的等离子体形状控制创建了实时虚拟电路。该方法使用大量的模拟等离子体平衡数据集来训练模拟器，模拟器可以快速推导出准确的虚拟电路，克服了预计算电路的局限性，这些电路在等离子体条件偏离参考点时性能会下降。经过验证的模拟器显示出高精度和正交性，为实时等离子体控制提供了一种可扩展且通用的替代方案。 AI

影响 这项研究可能导致聚变反应堆中更稳定、更高效的等离子体控制，从而加速实现可行聚变能源的进展。

排序理由 该集群包含一篇学术论文，详细介绍了使用神经网络进行等离子体控制的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

神经网络实现聚变反应堆等离子体实时控制

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该集群包含一篇学术论文，详细介绍了使用神经网络进行等离子体控制的新方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Alasdair Ross, George K. Holt, Kamran Pentland, Adriano Agnello, Nicola C. Amorisco, Pedro Cavestany, Aran Garrod, Timothy Nunn, Charles Vincent, Graham McArdle ·

    用于通过神经网络模拟器进行等离子体形状控制的实时虚拟电路

    arXiv:2605.14939v2 Announce Type: replace-cross Abstract: Reliable position and shape control in tokamak plasmas requires accurate real-time regulation of several strongly coupled shape parameters. The control vectors that disentangle these couplings, referred to as \textit{virtu…

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